Triple

T4742865
Position Surface form Disambiguated ID Type / Status
Subject Universidad Nacional Agraria La Molina E105287 entity
Predicate shortName P43 FINISHED
Object UNALM
UNALM is a leading Peruvian public university specializing in agricultural, environmental, and related sciences.
 E467169 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: UNALM | Statement: [Universidad Nacional Agraria La Molina, shortName, UNALM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: UNALM
Context triple: [Universidad Nacional Agraria La Molina, shortName, UNALM]
  • A. UNA
    UNA is the stock ticker symbol for Unilever, a major multinational consumer goods company known for its wide range of food, personal care, and household products.
  • B. UNA
    UNA is a public university located in Florence, Alabama, known for its regional academic programs and historic campus.
  • C. UNISWA
    UNISWA is the commonly used acronym for the University of Swaziland, the national public university of Eswatini.
  • D. UNV
    UNV is the United Nations Volunteers programme, which mobilizes volunteers worldwide to support peace and development efforts under the UN system.
  • E. UNIL
    UNIL is the commonly used abbreviation for the University of Lausanne, a major public research university in Lausanne, Switzerland.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: UNALM
Triple: [Universidad Nacional Agraria La Molina, shortName, UNALM]
Generated description
UNALM is a leading Peruvian public university specializing in agricultural, environmental, and related sciences.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: UNALM
Target entity description: UNALM is a leading Peruvian public university specializing in agricultural, environmental, and related sciences.
  • A. UNA
    UNA is a public university located in Florence, Alabama, known for its regional academic programs and historic campus.
  • B. UNA
    UNA is the stock ticker symbol for Unilever, a major multinational consumer goods company known for its wide range of food, personal care, and household products.
  • C. UNISWA
    UNISWA is the commonly used acronym for the University of Swaziland, the national public university of Eswatini.
  • D. UNV
    UNV is the United Nations Volunteers programme, which mobilizes volunteers worldwide to support peace and development efforts under the UN system.
  • E. UNIL
    UNIL is the commonly used abbreviation for the University of Lausanne, a major public research university in Lausanne, Switzerland.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69bd43ef87a48190a5bc3600711aa032 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd64a85e9c81908e9c7bbbb998953e completed March 20, 2026, 3:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69be3a309a408190836c51d0fe85c5d8 completed March 21, 2026, 6:26 a.m.
NEDg Description generation batch_69be3d30efb4819088121ce087344da3 completed March 21, 2026, 6:39 a.m.
NED2 Entity disambiguation (via description) batch_69be3d99a288819088e42e04de5c17a4 completed March 21, 2026, 6:41 a.m.
Created at: March 20, 2026, 1:19 p.m.